Thursday, January 16, 2014

Advertising is a powerful form of marketingcommunication used to "encourage, persuade, or even manipulate an audience to take or continue to take some action". The final desired result is to drive consumer behavior with respect to a commercial offering, although political and ideological advertising is also common. The marketing mix has been the key concept to advertising. Themarketingmixrefers to four variables (the 4 P's) thata marketingmanagercancontrol in order toinfluence
abrand’ssalesormarketshare. The basic questionthatmanagers face nowadays is,
whatlevelorcombinationofthesevariables
maximizessales,marketshare,orprofit? Or, otherwise, "Howdosalesormarket
sharerespondtopastlevelsoforexpenditures
onthesevariables"?Researchershave
developedavarietyofeconometricmodelsofmarketresponsetothemarketingmix, mostof thesewhichhavefocusedonmarketresponse toadvertising or pricing(Sethuraman, 1991).Thereasonmaybethatexpenditures onthesevariablesseemthemostdiscretionary, somarketingmanagersaremostconcerned abouthowtheymanagethesevariables. Thebasicphilosophyunderlyingtheapproach
ofresponsemodelingisthatpastdataonconsumerandmarketresponsetothemarketing mixcontainvaluableinformationthatcan
enlightenourunderstandingofresponse.Seven response models to advertising are have been already patternalized: Current,shape,competitive,carryover,dynamic,contentandmediaeffects of advertising.Thefirstfour arecommonacrosspriceand the othermarketing
variables.Thelastthreeareuniquetoadvertising. Current and Carryover Effect

Thecurrenteffectofadvertisingisthechangeinsalescausedbyanexposureofadvertisingoccurringatthesame timeperiodastheexposure. The x-axis here is time, whilesales are onthey-axis andthebaselinesalesarethedashed line.Thecurrenteffectofadvertisingisthe
spikeinsalesfromthebaselinegivenanexposureofadvertising. Decades ofresearchindicatethatthiseffectofadvertisingissmallrelativetothatofothermarketing
variablesandquitefragile, as it can be easilydrownedoutbythe noiseinthedata. It can be captured by the model:Yt=a+b1At+b2Pt+b3Rt+b4Qt+ etwhereYrepresentsthe dependent
variable (e.g. sales),whiletheothercapitallettersrepresentvariablesofthemarketingmix,suchasadvertising
(A),price(P),salespromotion(R),orquality(Q).
Theparametersaandbkarecoefficientsthatthe researcherwantstoestimate.bkrepresentstheeffectoftheindependentvariablesonthedependentvariable,wherethesubscriptkisanindexfortheindependentvariables. etareerrors that can be approached as "white noise".

Theshapeoftheeffectreferstothechange
insalesinresponsetoincreasingintensityof
advertisinginthesametimeperiod.Theintensity ofadvertising
couldbeintheformofexposuresperunittimeandisalsocalledfrequency
orweight. The x-axisnowistheintensityofadvertisingina period,whilethey-axisistheresponseofsales. It can be captured by the exponential attraction model:

Advertisingnormallytakesplaceinfree markets.Wheneveronebrandadvertisesasuccessfulinnovationorsuccessfullyusesanew
advertisingform,otherbrandsquicklyimitate it.Competitiveadvertisingtendstoincreasethe noiseinthemarketandthusreducetheeffectivenessofanyonebrand’sadvertising.The competitiveeffectofatargetbrand’sadvertising isitseffectivenessrelativetothatoftheother
brandsinthemarket.Thesimplestmethod
ofcapturingadvertisingresponseincompetition istomeasureandmodelsalesandadvertisingof
thetargetbrandrelativetoallotherbrandsinthe
market with more complex models, mainly based on the aforementioned econometric model of the "Shape Effect". These first four models may also apply to "Price" instead of "Sales" dependent variable.

The last three effects (dynamic, content, media) may be captured by models similar to the S-shaped response with modeling interactions integrated due to the competitive environment or even competitive distributed lag Models, however in reality their mathematics can be quite complex (Tellis, 2006).

Conclusion

Prudentmarketingmanagers need to takeinto accounthowmarketshaverespondedtothe
marketingmixinthepast. Past may predict futurewith relative certaintybutit also containsvaluable
lessonsthatmightenlightenthefuture. The aforementioned econometricsofresponsemodelingdescribehowaresearchershouldmodel
responsetothemarketingmix and especially to advertising in order tocapture and control themostimportant effectsvalidly. Which may be the "raison d'être" for marketing managers, in the first place.